diff --git a/dnc/sparse_memory.py b/dnc/sparse_memory.py
index d06e975..76cb55e 100644
--- a/dnc/sparse_memory.py
+++ b/dnc/sparse_memory.py
@@ -64,6 +64,7 @@ class SparseMemory(nn.Module):
     self.I = cuda(1 - T.eye(self.c).unsqueeze(0), gpu_id=self.gpu_id)  # (1 * n * n)
     self.δ = 0.005  # minimum usage
     self.timestep = 0
+    self.mem_limit_reached = False
 
   def rebuild_indexes(self, hidden, erase=False):
     b = hidden['memory'].size(0)
@@ -95,6 +96,7 @@ class SparseMemory(nn.Module):
         i.add(hidden['memory'][n], last=pos[n][-1])
     else:
       self.timestep = 0
+      self.mem_limit_reached = False
 
     return hidden
 
@@ -155,11 +157,12 @@ class SparseMemory(nn.Module):
     for batch in range(b):
       # update indexes
       hidden['indexes'][batch].reset()
-      hidden['indexes'][batch].add(hidden['memory'][batch], last=pos[batch][-1])
+      hidden['indexes'][batch].add(hidden['memory'][batch], last=(pos[batch][-1] if not self.mem_limit_reached else None))
 
     mem_limit_reached = hidden['least_used_mem'][0].data.cpu().numpy()[0] >= self.mem_size - 1
     hidden['least_used_mem'] = (hidden['least_used_mem'] * 0 + self.c +
                                 1) if mem_limit_reached else hidden['least_used_mem'] + 1
+    self.mem_limit_reached = mem_limit_reached or self.mem_limit_reached
 
     return hidden
 
diff --git a/dnc/sparse_temporal_memory.py b/dnc/sparse_temporal_memory.py
index 2ddac8d..91555f0 100644
--- a/dnc/sparse_temporal_memory.py
+++ b/dnc/sparse_temporal_memory.py
@@ -67,6 +67,7 @@ class SparseTemporalMemory(nn.Module):
     self.I = cuda(1 - T.eye(self.c).unsqueeze(0), gpu_id=self.gpu_id)  # (1 * n * n)
     self.δ = 0.005  # minimum usage
     self.timestep = 0
+    self.mem_limit_reached = False
 
   def rebuild_indexes(self, hidden, erase=False):
     b = hidden['memory'].size(0)
@@ -98,6 +99,7 @@ class SparseTemporalMemory(nn.Module):
         i.add(hidden['memory'][n], last=pos[n][-1])
     else:
       self.timestep = 0
+      self.mem_limit_reached = False
 
     return hidden
 
@@ -167,11 +169,12 @@ class SparseTemporalMemory(nn.Module):
     for batch in range(b):
       # update indexes
       hidden['indexes'][batch].reset()
-      hidden['indexes'][batch].add(hidden['memory'][batch], last=pos[batch][-1])
+      hidden['indexes'][batch].add(hidden['memory'][batch], last=(pos[batch][-1] if not self.mem_limit_reached else None))
 
     mem_limit_reached = hidden['least_used_mem'][0].data.cpu().numpy()[0] >= self.mem_size - 1
     hidden['least_used_mem'] = (hidden['least_used_mem'] * 0 + self.c +
                                 1) if mem_limit_reached else hidden['least_used_mem'] + 1
+    self.mem_limit_reached = mem_limit_reached or self.mem_limit_reached
 
     return hidden